Atmos. Chem. Phys., 19, 7233–7254, 2019 https://doi.org/10.5194/acp-19-7233-2019 © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.

Ozone and carbon monoxide observations over open oceans on R/V Mirai from 67◦ S to 75◦ N during 2012 to 2017: testing global chemical reanalysis in terms of Arctic processes, low ozone levels at low latitudes, and pollution transport

Yugo Kanaya1, Kazuyuki Miyazaki2,1, Fumikazu Taketani1, Takuma Miyakawa1, Hisahiro Takashima1,3, Yuichi Komazaki1, Xiaole Pan1,a, Saki Kato3, Kengo Sudo1,4, Takashi Sekiya1, Jun Inoue5, Kazutoshi Sato6, and Kazuhiro Oshima1,b 1Research Institute for Global Change (RIGC), Japan Agency for Marine–Earth Science and Technology (JAMSTEC), Yokohama 2360001, Japan 2Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA 3Faculty of Science, Fukuoka University, Fukuoka 8140133, Japan 4Graduate School of Environmental Studies, Nagoya University, Nagoya 4648601, Japan 5Arctic Environment Research Center, National Institute of Polar Research, Tachikawa 1908518, Japan 6School of Earth, Energy and Environmental Engineering, Kitami Institute of Technology, Kitami 0908507, Japan anow at: Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, bnow at: Department of Radioecology, Institute of Environmental Sciences, Rokkasho 0393212, Japan

Correspondence: Yugo Kanaya ([email protected])

Received: 27 December 2018 – Discussion started: 14 January 2019 Revised: 6 May 2019 – Accepted: 9 May 2019 – Published: 3 June 2019

Abstract. Constraints from ozone (O3) observations over fects of forest fires and fossil fuel combustion were recog- oceans are needed in addition to those from terrestrial re- nized, TCR-2 gave an excellent performance in reproducing gions to fully understand global tropospheric chemistry and the observed temporal variations and photochemical buildup its impact on the climate. Here, we provide a large data set of of O3 when assessed from 1O3/1CO ratios. For clean ma- ozone and carbon monoxide (CO) levels observed (for 11 666 rine conditions with low and stable CO mixing ratios, two and 10 681 h, respectively) over oceans. The data set is de- focused analyses were performed. The first was in the Arc- rived from observations made during 24 research cruise legs tic (> 70◦ N) in September every year from 2013 to 2016; of R/V Mirai during 2012 to 2017, in the Southern, Indian, TCR-2 underpredicted O3 levels by 6.7 ppbv (21 %) on aver- ◦ Pacific, and Arctic oceans, covering the region from 67 S age. The observed vertical profiles from O3 soundings from to 75◦ N. The data are suitable for critical evaluation of the R/V Mirai during September 2014 had less steep vertical over-ocean distribution of ozone derived from global atmo- gradients at low altitudes (> 850 hPa) than those obtained spheric chemistry models. We first give an overview of the by TCR-2. This suggests the possibility of a more efficient statistics in the data set and highlight key features in terms descent of the O3-rich air from above than assumed in the of geographical distribution and air mass type. We then use models. For TCR-2 (CHASER), dry deposition on the Arc- the data set to evaluate ozone mixing ratio fields from the tic ocean surface might also have been overestimated. In the tropospheric chemistry reanalysis version 2 (TCR-2), pro- second analysis, over the western Pacific equatorial region ◦ ◦ ◦ duced by assimilating a suite of satellite observations of (125–165 E, 10 S to 25 N), the observed O3 level more multiple species into a global atmospheric chemistry model, frequently decreased to less than 10 ppbv in comparison to namely CHASER. For long-range transport of polluted air that obtained with TCR-2 and also those obtained in most masses from continents to the oceans, during which the ef- of the Atmospheric Chemistry Climate Model Intercompari-

Published by Copernicus Publications on behalf of the European Geosciences Union. 7234 Y. Kanaya et al.: Ozone and carbon monoxide over open oceans: observations and model evaluation son Project (ACCMIP) model runs for the decade from 2000. Alert (82.45◦ N, 62.51◦ W), Barrow (71.32◦ N, 156.61◦ W), These results imply loss processes that are unaccounted for Zeppelin (78.90◦ N, 11.88◦ E), Pallas–Sodankyla (67.97◦ N, in the models. We found that the model’s positive bias pos- 24.12◦ E), Summit (72.58◦ N, 38.46◦ W) and Thule (76.5◦ N, itively correlated with the daytime residence times of air 68.8◦ W) were used to test simulations. Measurements from masses over a particular grid, namely 165–180◦ E and 15– individual cruises (e.g., Dickerson et al., 1999; Kobayashi et 30◦ N; an additional loss rate of 0.25 ppbv h−1 in the grid best al., 2008; Boylan et al., 2015; Prados-Roman et al., 2015), a explained the gap. Halogen chemistry, which is commonly large collection from multiple cruises (e.g., Lelieveld et al., omitted from currently used models, might be active in this 2004), O3 soundings from the SHADOZ network (e.g., Olt- region and could have contributed to additional losses. Our mans et al., 2001; Thompson et al., 2017), and those from open data set covering wide ocean regions is complemen- various campaigns (e.g., Kley et al., 1996; Takashima et al., tary to the Tropospheric Ozone Assessment Report data set, 2008; Rex et al., 2014) have provided important O3 data which basically comprises ground-based observations and over oceanic regions. However, their spatiotemporal cover- enables a fully global study of the behavior of O3. age over open oceans is too sparse to complete the global pic- ture. Aircraft observations (e.g., HIAPER Pole-to-Pole Ob- servations (HIPPO); Wofsy et al., 2011) also sampled ma- rine boundary layer but the measurement frequency was not 1 Introduction necessarily high. One mature example of such global obser- vations that include the over-ocean atmosphere is that for The global burden and distribution of tropospheric ozone CO2. For example, observational data at a large number of (O3) have changed from preindustrial times to the present, remote islands are available from the World Data Centre for and have induced a radiative forcing of +0.4 ± 0.2 W m−2 Greenhouse Gases (WDCGG) database of the World Me- (IPCC, 2013) by interactions with the Earth’s radiative field. teorological Organization (WMO)/GAW. Atmospheric CO2 The distribution of O3 is critical for determining concentra- measurements are now accepted by SOCAT Version 4 (https: tion fields of hydroxyl radicals, which control the lifetimes //www.socat.info/, last access: 27 May 2019), which is a of many important chemical species, including methane. database of ship-based observations, e.g., from research ves- Changes in atmospheric chemistry and their impacts on the sels and voluntary ships. Similarly dense O3 observations climate are often investigated by using O3 distributions de- over oceans are needed. rived from global atmospheric chemistry model simulations. An understanding of the processes behind the O3 mixing Therefore the model performance determines the accuracy ratio distribution is important. Young et al. (2018) reported of the assessment, requiring model evaluation against field that the rates of chemical processes (production and loss) observations of levels of O3 and its precursors. For exam- and deposition/stratosphere–troposphere exchange could dif- ple, the models included in the Atmospheric Chemistry Cli- fer among models by factors of 2–3. More observational con- mate Model Intercomparison Project (ACCMIP; Shindell et straints for characterizing photochemical buildup and long- al., 2011; Lamarque et al., 2013) and the Chemistry–Climate range transport events using tracers such as carbon monox- Model Initiative (CCMI; Morgenstein et al., 2017) were care- ide (CO) are required. The chemical loss term under clean fully evaluated against field observations (e.g., Tilmes et al., marine conditions should also be examined; the loss rate 2016). Recently, an unprecedented comprehensive data set caused by halogen chemistry and the regions where such of O3 measurements was systematically compiled under a chemistry is important need to be evaluated. community-wide activity, i.e., the Tropospheric Ozone As- Since 2010, we have conducted ship-borne observations sessment Report (TOAR) (Cooper et al., 2014; Schultz et al., on R/V Mirai of the atmospheric composition, including the 2017; Gaudel et al., 2018), and this provided additional con- O3 and CO levels, for more than 10 000 h. The geographi- straints for model simulations. cal coverage was wide, covering the Arctic, Pacific, Indian, However, even with the data in the TOAR, observa- and Southern oceans. Such observations, together with cur- tion data coverage over oceans is still poor; Schultz et rently available data sets, will enable critical testing of model al. (2017) reported that the “true oceanic sites” covered simulations that cover the entire globe. In this paper, we ◦ ◦ by TOAR were American Samoa (14.25 S, 170.56 W), present our observational data set for O3 and CO for the Sable Island (43.93◦ N, 59.90◦ W), the Ieodo Ocean Re- first time. The data were separately analyzed for cases af- search Station (32.12◦ N, 125.18◦ E), Ogasawara (27.08◦ N, fected by long-range transport and those under clean marine 142.22◦ E), and Minamitori Island (24.28◦ N, 153.98◦ E), conditions. For each case, the observations were compared while Cape Grim (40.68◦ S, 144.69◦ E), Amsterdam Island with independent reanalysis data from Tropospheric Chem- (37.80◦ S, 77.54◦ E), and Mace Head (53.33◦ N, 9.90◦ W) istry Reanalysis version 2 (TCR-2). The aims are to interpret were also included in other categories. For assessment the observations and to evaluate the reanalysis data over the of the Arctic region (AMAP, 2015), observations ob- oceans. The reanalysis data were produced by assimilating tained truly over the were largely unavail- a suite of satellite data for O3 and precursors into a global able; only observations at coastal or inland sites such as atmospheric chemistry model, namely CHASER. The pre-

Atmos. Chem. Phys., 19, 7233–7254, 2019 www.atmos-chem-phys.net/19/7233/2019/ Y. Kanaya et al.: Ozone and carbon monoxide over open oceans: observations and model evaluation 7235 cursor emissions were simultaneously optimized. This has ment was calibrated twice per year in the laboratory, before advantages over forward model simulations incorporating a and after deployment, using a primary standard O3 genera- bottom-up emission inventory because realistic emissions are tor (Model 49PS, Thermo Scientific, Waltham, MA, USA). taken into account, even those for recent years, for which a The CO instrument was calibrated on board twice per year, bottom-up emission inventory is not yet ready. TCR-2 was on embarking and disembarking of the instrument, using updated from the previous version, TCR-1 (Miyazaki et al., a premixed standard gas (CO/N2, 1.02 ppm, Taiyo-Nissan, 2015): the spatial resolution has been improved and newer Tokyo, Japan). The reproducibility of the calibration was to satellite products are used for assimilation. For TCR-1, eval- within 1 % for O3 and 3 % for CO. uation against surface, sonde, and aircraft observations was The 24 cruise legs during which the two instruments were successful (Miyazaki et al., 2015; Miyazaki and Bowman, operated are listed in Table 1. During MR12-02 Legs 1 and 2017). For TCR-2, the performance has been evaluated using 2, the CO instrument did not work well and only the O3 data the KORUS-AQ aircraft campaign measurements over east were used for analysis. The cruise regions ranged widely, (Miyazaki et al., 2019). However, insufficient evalua- from the Arctic, the north, the , South Pacific Ocean, tion against data over remote oceans has been performed and and the eastern part of the to the Southern our motivation in this study was to attempt this. Ocean. The Arctic cruises took place every year during the In Sect. 2, field observations and the assimilation period 2013 to 2016 (specifically during the MR13-06, 14- model are outlined. In Sect. 3, geographical and statistical 05, 15-03, and 16-06 cruises). Other cruises aimed to study overviews of the observational data are presented and then geology, meteorology, and oceanography and took place in compared with the data from TCR-2. CO data and backward the Pacific, Indian, and Southern oceans. The western Pacific trajectories are used to classify O3 data into cases that are in- equatorial region and Indian oceans were also frequently vis- fluenced by long-range transport of pollution from continents ited for operation of the TRITON buoy. Regions near Japan and other cases, namely clean remote air masses. For the for- were frequently observed because the departure and arrival mer cases, the reproducibility of the O3 mixing ratio levels ports were often in that country. Our data basically did not and whether the chemical buildup is well reproduced by the include observations made while the vessel was anchored in reanalysis were tested for more than 20 events. For the latter ports; exceptions were the inclusion of short on-port data cases, a particular focus was placed on underestimation for when the ports were visited during cruise legs (see the far- the Arctic Ocean and overestimation for the western Pacific right-hand column in Table 1). During many cruises, other equatorial region by TCR-2. Similar trends were observed instruments, i.e., for performing black carbon and fluores- with the ensemble median of model runs of ACCMIP. Possi- cent aerosol measurements, and multi-axis differential opti- ble explanations for these discrepancies were investigated. cal absorption spectroscopy (MAX-DOAS), were operated together (e.g., Taketani et al., 2016; Takashima et al., 2016). These data will be reported in future publications. 2 Methodology 2.2 Reanalysis and ACCMIP models 2.1 Observations on R/V Mirai The first version of tropospheric chemistry reanalysis from Atmospheric composition observations were conducted on JAMSTEC, i.e., TCR-1, which used an ensemble Kalman R/V Mirai (8706 gross tons) of the Japan Agency for filter (EnKF) approach with a global atmospheric chem- Marine–Earth Science and Technology (JAMSTEC) from istry model (CHASER) as a base forward model, has been 2010. The O3 and CO levels were determined by UV and previously described (Miyazaki et al., 2015). Here, the up- IR absorption methods (Models 49C and 48C, Thermo Sci- dated version, TCR-2, was used (Miyazaki et al., 2019, entific, Waltham, MA, USA), respectively. The instruments https://ebcrpa.jamstec.go.jp/tcr2/about_data.html, last acces: were located in an observational room on the top floor. Two 27 May 2019). The detailed description of the basic data Teflon tubes (6.35 mm o.d.) of length ∼ 20 m were used to assimilation framework and the evaluation results using the sample air near the bow to best avoid contamination from KORUS-AQ aircraft measurements over east Asia are avail- the ship’s exhaust. The exhaust effect was clearly discerned able in Miyazaki et al. (2019), while detailed global evalua- in the 1 min O3 data record as high concentrations of NO tions are ongoing. The major aspects of the update of TCR- ◦ in the exhaust titrated O3. Minute data exceeding 3σ of the 1 were a finer horizontal resolution (1.1 , compared with standard deviation in an hour were eliminated before produc- 2.8◦ in TCR-1), assimilation of newer satellite data prod- ing hourly averages. The CO data for the same minutes were ucts – OMI NO2 (QA4ECV), GOME-2 NO2 (TM4NO2A removed. The CO instrument alternately measured the am- v2.3), TES O3 (v6), MOPITT CO (v7 NIR), and MLS O3, bient (for 40 min) and zero (for 20 min) levels. For the zero- HNO3 (v4.2) – and extension of the period to 2017 (from level observations, CO was removed from the ambient air by 2005). A priori emissions were obtained from EDGAR v4.2 using a zero-air generator equipped with a heated Pt cata- for anthropogenic sources, GFED v3.1 for open-fire emis- lyst (Model 96, Nippon Thermo, Uji, Japan). The O3 instru- sions, and GEIA for biogenic sources. In addition to con- www.atmos-chem-phys.net/19/7233/2019/ Atmos. Chem. Phys., 19, 7233–7254, 2019 7236 Y. Kanaya et al.: Ozone and carbon monoxide over open oceans: observations and model evaluation

Table 1. Overview of cruise legs of R/V Mirai used in this study.

Cruise Study area Departure Arrival Remark MR12-02 Leg1 Western North Pacific 00:00 UTC Mutsu 08:00 UTC Onahama (out of port) 4 Jun 2012 24 Jun 2012 MR12-02 Leg2 Western North Pacific 08:00 UTC Onahama 00:00 UTC Mutsu Hachinohe Port from 00:30 to 24 Jun 2012 (out of 12 Jul 2012 08:00 UTC 11 Jul (no data) port) MR13-04 Western North Pacific 23:50 UTC Yokohama 00:00 UTC Mutsu 9 Jul 2013 29 Jul 2013 MR13-05 Bering Sea 23:50 UTC Mutsu 17:40 UTC Dutch Harbor 12 Aug 2013 26 Aug 2013 MR13-06 Leg1 Arctic Ocean, Bering 18:00 UTC Dutch 18:40 UTC Dutch Harbor Sea 28 Aug 2013 Harbor 7 Oct 2013 MR13-06 Leg2 Bering Sea, North 17:40 UTC Dutch 23:50 UTC Mutsu Pacific 9 Oct 2013 Harbor 20 Oct 2013 MR14-01 East Indian Ocean, 23:00 UTC Mutsu 00:00 UTC Palau equatorial region 8 Jan 2014 13 Feb 2014 MR14-02 Western Pacific, 00:00 UTC Koror, 00:00 UTC Mutsu Hachinohe Port, 04:00–09:00 UTC equatorial region 15 Feb 2014 Palau 23 Mar 2014 21 Mar 2014 (no data) MR14-04 Leg1 Western North Pacific 22:10 UTC Yokohama 04:00 UTC Kushiro 8 Jul 2014 15 Jul 2014 MR14-04 Leg2 North Pacific 01:00 UTC Kushiro 17:50 UTC Dutch Harbor 17 Jul 2014 29 Aug 2014 MR14-05 Arctic Ocean, Bering 18:10 UTC Dutch Har- 00:20 UTC Yokohama Sea, North Pacific 31 Aug 2014 bor 10 Oct 2014 MR14-06 Leg1 Western Pacific, 06:10 UTC Mutsu 23:20 UTC Chuuk Yokohama Port, from 23:10 UTC 5 equatorial region 4 Nov 2014 17 Dec 2014 Nov to 07:00 UTC 7 Nov (with data) MR14-06 Leg2 Western Pacific 00:07 UTC Chuuk 00:10 UTC Palau equatorial region 20 Dec 2014 19 Jan 2015 MR14-06 Leg3 Western Pacific, East 00:00 UTC Palau 00:00 UTC Mutsu Hachinohe Port, from 23:30 UTC Indian Ocean 22 Jan 2015 25 Feb 2015 23 Feb to 07:00 UTC 24 Feb (with equatorial region data) MR15-03 leg 1 North Pacific, Bering 22:50 UTC Mutsu 18:50 UTC Dutch Harbor Sea, Arctic Ocean 23 Aug 2015 6 Oct 2015 MR15-03 leg 2 Bering Sea, North 18:10 UTC Dutch 23:50 UTC Mutsu Hachinohe Port, from 23:00 UTC Pacific 9 Oct 2015 Harbor 21 Oct 2015 20 Oct to 06:50 UTC 21 Oct (with data) MR15-04 Western Pacific, East 06:00 UTC Mutsu 02:20 UTC Jakarta Hachinohe Port, from 22:50 UTC Indian Ocean equato- 5 Nov 2015 20 Dec 2015 5 Nov to 06:20 UTC 6 Nov (with rial region data) MR15-05 leg 1 East Indian Ocean 03:10 UTC Jakarta 00:50 UTC Bali 23 Dec 2015 11 Jan 2016 MR15-05 leg 2 East Indian Ocean, 01:00 UTC Benoa, Bali 23:50 UTC Yokohama Western North Pacific 13 Jan 2016 24 Jan 2016 MR16-06 Arctic Ocean, Bering 00:00 UTC Hachinohe 00:00 UTC Mutsu Nome port, 16:00–20:10 UTC Sea, North Pacific 22 Aug 2016 5 Oct 2016 23 Sep (with data); Hachinohe Port from 22:30 UTC 3 Oct to 07:20 UTC 4 Oct (with data) MR16-08 Western Pacific 07:00 UTC Shimizu 21:00 UTC Suva equatorial region 27 Nov 2016 23 Dec 2016 MR16-09 leg 1 South Pacific 17:10 UTC Suva 11:00 UTC Puerto Mont 26 Dec 2016 17 Jan 2017 MR16-09 leg 3 13:10 UTC Punta 21:00 UTC Auckland 8 Feb 2017 Arenas 4 Mar 2017 MR16-09 leg 4 Western Pacific 21:20 UTC Auckland 00:00 UTC Mutsu Hachinohe Port, from 22:40 UTC 7 Mar 2017 28 Mar 2017 26 Mar to 06:50 UTC 27 Mar (with data)

Atmos. Chem. Phys., 19, 7233–7254, 2019 www.atmos-chem-phys.net/19/7233/2019/ Y. Kanaya et al.: Ozone and carbon monoxide over open oceans: observations and model evaluation 7237 centration fields of chemical species, NOx emissions (sur- Particle Lagrangian Integrated Trajectory (HYSPLIT) model face and lightning, separately) and CO were included in the (Draxler and Rolph, 2013) to trace the origin areas of the state vector and were simultaneously optimized. An advan- observed air masses. GDAS1 three-dimensional meteorolog- tage was that analysis for recent years (e.g., 2017) was pos- ical field data with a resolution of 1.0◦ were used. Cases sible before development of a bottom-up emission inventory. that did not involve traveling over land regions (at alti- The base forward model CHASER V4.0 used for TCR-2 has tudes lower than 2500 m a.s.l.) during the 5 days were ex- been described by Sekiya et al. (2018). Briefly, 93 species tracted as marine air mass cases. Here, the land mask data and 263 reactions (including heterogeneous reactions) rep- from NASA (https://ldas.gsfc.nasa.gov/gldas/data/0.25deg/ resent Ox−NOx−HOx−CH4−CO photochemistry and ox- landmask_mod44w_025.asc, last access: 27 May 2019) at a idation of nonmethane volatile organic compounds. Tropo- resolution of 0.25◦ were used for making judgments. spheric halogen chemistry is not included. The dry deposi- −1 tion velocity (vd) of O3 was computed as (ra + rb + rs) , where ra, rb, and rs are the aerodynamic resistance, the sur- 3 Results and discussion face canopy (quasi-laminar) layer resistance, and the surface resistance, respectively (Wesely, 1989). 1/rs over ocean sur- 3.1 Overview of geographical distributions of O3 and face was assumed to be 0.075 cm s−1 globally, irrespective of CO −1 region (Sudo et al., 2002). As a result, vd was ∼ 0.04 cm s over the Arctic open ocean in September, for instance. This Figure 1a shows the entire O3 data set from observations will be a subject of discussion in Sect. 3.3.2. on R/V Mirai from 2012 to 2017. The covered latitudinal ◦ Because the number of assimilated TES O3 retrievals de- range was wide, from 67.00 S (at 06:00 UTC on 16 Febru- creased substantially after 2010, the data assimilation per- ary 2017 during MR16-09 Leg 3) to 75.12◦ N (at 06:00 UTC formance became worse after 2010 in the previous version on 6 September 2014 during MR14-05). The highest hourly TCR-1 (Miyazaki et al., 2015), and it can be expected that mixing ratio, i.e. 66.6 ppbv, was recorded twice: first at ◦ ◦ TCR-2 has similar increases in O3 analysis errors after 2010. 35.89 N, 141.95 E, about 70 km east off the coast of the Nevertheless, the multi-constituent data assimilation frame- Kanto area, Japan, at 04:00 UTC on 6 July 2012, and sec- work provides comprehensive constraints on the chemical ond at 32.29◦ N, 146.04◦ E, about 500 km southeast of the system and entire tropospheric O3 profiles through correc- Kanto area at 14:00 UTC on 18 March 2014. During 57 h, tions made to precursors’ emissions and stratospheric con- the hourly values exceeded 60 ppbv (which corresponds to centrations, as demonstrated by Miyazaki et al. (2015, 2019). the environmental standard in Japan) in a similar region off We also used the monthly ACCMIP ensemble simula- the coast of Japan, under the influence of Asian regional air tions for the present day (Shindell et al., 2011), which were pollution. The lowest hourly mixing ratio, i.e. 4.3 ppbv, was represented as simulation results for a decade from 2000 recorded twice on the western Pacific equatorial region: first (Stevenson et al., 2013; Young et al., 2013). The monthly at 5.86◦ N, 156.00◦ E and secondly at 7.96◦ N, 156.02◦ E at mean O3 field from an ensemble member, MIROC-Chem, 09:00 and 21:00 UTC, respectively, on 11 March 2014. Val- with a modeling framework similar to that of TCR-2, pro- ues lower than 10 ppbv were recorded for a total of 800 h; vided corresponding climatological mixing ratio levels at a this will be discussed in the following section. given location. These values were used to evaluate the per- Figure 2a shows the entire CO data set. The highest mix- formance of TCR-2, which uses meteorological data and es- ing ratio was 556 ppbv, which was recorded at 58.00◦ N, timated emissions in those particular years. Seven other AC- 179.23◦ E, at 01:00 UTC on 26 September 2016 during the CMIP ensemble members that provide hourly O3 mixing ra- MR16-06 cruise, where a dense plume from severe forest tios at the Earth’s surface (CESM-CAM-superfast, CMAM, fires in reached as far as the Bering Sea. All 8 h in GEOSCCM, GFDL-AM3, GISS-E2-R, MOCAGE, and UM- which the mixing ratio exceeded 500 ppbv were recorded on CAM) were also used for comparative analysis in terms of the same day. There were 59 other hours when the CO mix- frequency distribution of O3 mixing ratios in the Arctic re- ing ratio exceeded 300 ppbv, when anthropogenic emissions gion (domain 1, 72.5–77.5◦ N, 190–205◦ E) and in a nar- from east Asia and/or biomass burning were important. ◦ row western Pacific equatorial region (domain 3, 0–15 N, Figure 3 shows an example of O3 variations for data 150–165◦ E). The ACCMIP results were chosen for the lat- from MR14-06 Leg 1 with backward trajectories. The ves- est intercomparison exercises because the data were publicly sel started from Mutsu port (41.37◦ N, 141.24◦ E), stayed for available. about 32 h at Yokohama port (35.45◦ N, 139.66◦ E), and then headed to the western Pacific equatorial region. A latitudi- 2.3 Backward trajectory nal gradient was apparent: north of 27◦ N was dominated by air masses originating from the Asian continent, as shown by Five-day backward trajectories from an altitude of 500 m violet trajectory lines. During some hours, high levels, i.e., above sea level (a.s.l.) were calculated every hour from the greater than 50 ppbv of O3, were recorded (points with red position of R/V Mirai by using NOAA’s Hybrid Single- trajectory lines). In contrast, marine air masses from the east www.atmos-chem-phys.net/19/7233/2019/ Atmos. Chem. Phys., 19, 7233–7254, 2019 7238 Y. Kanaya et al.: Ozone and carbon monoxide over open oceans: observations and model evaluation

Figure 1. Geographical distributions from (a) observed hourly O3 mixing ratios (N = 11 666) on R/V Mirai during 24 research cruise legs in 2012–2017 and (b) those from reanalysis (TCR-2) of data along R/V Mirai cruise track; (c) reanalysis/observation ratios (TCR-2/obs) for O3 mixing ratios. In (a) stationary points of TOAR data set are plotted (magenta dots). In (a) and (c), three green rectangles show focused domains in the Arctic (domain 1, 72.5–77.5◦ N, 190–205◦ E) and two in the western Pacific equatorial region (domain 2, 10◦ S to 25◦ N, 125–165◦ E; domain 3, 0–15◦ N, 150–165◦ E). were dominant south of 27◦ N and the mixing ratio levels de- as marine and other cases was satisfactory for identifying creased to less than 30 ppbv. South of 15◦ N, even lower lev- cases of long-range transport of pollutants from continents, els were dominant, i.e., < 15 ppbv, particularly in equatorial although some events with continental effects with traveling regions where levels less than 10 ppbv of O3 were frequently times longer than 120 h were probably wrongly categorized. observed. The latitudinal gradient, air mass exchange, and Because longer trajectories may not be reliable, we will use transport of photochemically produced O3 are the three im- this criterion (i.e., 120 h) in the following sections with a portant factors determining distributions. Figure S1 in the notice of such limitations. Stratospheric influences were not Supplement shows the spatial distributions of O3 and back- identified: we did not find any events with reasonable O3- ward trajectories for each cruise leg, and their time series. level enhancement accompanied by descent of air masses All three factors listed above for the MR14-06 Leg 1 had ma- from 8 km or higher altitudes within 72 h prior to observa- jor effects on the variations. The classification of air masses tions.

Atmos. Chem. Phys., 19, 7233–7254, 2019 www.atmos-chem-phys.net/19/7233/2019/ Y. Kanaya et al.: Ozone and carbon monoxide over open oceans: observations and model evaluation 7239

Figure 3. Observed O3 mixing ratios during MR14-06 Leg 1 and backward trajectories (120 h). Magenta lines indicate cases in which trajectory entered regions over land (at altitudes < 2500 m a.s.l.). Red lines indicate cases in which observed O3 mixing ratios ex- ceeded 50 ppbv.

rates were optimally estimated during the data assimilation cycle and were reflected in the mixing ratio field. The emis- sion changes provide substantial influences on ozone fore- casts over many regions. Assimilation of the TES ozone mea- surements has limited impacts on near-surface ozone owing to its weak sensitivity to the lower troposphere. In Fig. S1, the comparisons are shown as time-series plots. Excellent matches in the evolution with time of O3 and CO mixing ratios were found for the latter period of MR14-02, i.e., during the period 12–22 March 2014, in the time series Figure 2. Geographical distributions of (a) observed CO mixing ra- (Fig. S1g). The blue lines show plots of monthly climatolog- tios and (b) those from TCR-2. In (a) magenta boxes indicate 23 ical mean mixing ratios, which were obtained from MIROC- regions where 1O3/1CO ratios were analyzed (see Fig. 8 and Ta- Chem. Although the monthly means sometimes followed the ble 2). observed baseline trend for O3, the performance of TCR-2 was superior, particularly for reproducing detailed peak pat- terns for CO. This case will be analyzed in Sect. 3.3.1 on 3.2 Comparisons between observations and TCR-2 photochemical buildup. A similarly excellent performance data: Global features was obtained for MR15-05 Leg 2 (Fig. S1r) and MR16-09 Leg 4 (Fig. S1w), when the ship returned to Japan from the Figures 1b and 2b show the geographical distributions of O3 south. and CO obtained from TCR-2 along the cruise track. The Clear gaps were also sometimes observed. These are prob- nearest grid and time (2 h resolution) at the lowest layer were ably related to limited reproducibility in the meteorological sampled to achieve the best possible comparison with the ob- field and errors in the emission estimation and other physico- servations shown in Figs. 1a and 2a. Most features were in chemical processes that were taken into account in the model agreement with the observations, in terms of areas with high system. A large gap was observed during the latter half of mixing ratios and latitudinal gradients. This comparison in- the MR14-01 cruise (Fig. S1f); the predictions produced by dicates a reasonably high quality of reanalysis data over the TCR-2 for CO and O3 in the eastern Indian Ocean were too oceans. This is partly because the NOx and CO emissions high. The climatological mean from MIROC-Chem repro- www.atmos-chem-phys.net/19/7233/2019/ Atmos. Chem. Phys., 19, 7233–7254, 2019 7240 Y. Kanaya et al.: Ozone and carbon monoxide over open oceans: observations and model evaluation duced the observed level better, which suggests that false in- liers (latter half of MR14-01 and cases in which TCR-2 ex- formation was introduced from satellite observations to the ceeded 70 ppbv) were omitted (red, N = 11 305). The ex- surface mixing ratios, for instance, associated with the use cellent performance of TCR-2 was assured by a resolution of total column measurements and errors in vertical trans- of 2 h in reproducing O3 mixing ratio variations. When the port, or that the position of ITCZ was too far south in the data were further binned to a resolution of 1 day (with ob- simulation. During other cruises, smaller gaps in the peak servations for 6 h or more), R2 improved to 0.66; this sug- occurrence times and peak mixing ratio levels were found. gests that the original variability was partly derived from For example, during MR14-04 Leg 2 (Fig. S1i), the peak small shifts in the peak times by less than a day. In the times for O3 and CO during the period 27 July to 6 Au- past, reanalysis data were not used for such detailed diag- gust 2014 were out of phase by about 1 to 2 days. This noses but were normally compared with observations after was probably caused by a small displacement of pollution monthly averaging or binning to coarse latitudinal bands. air masses after long-range transport. High O3 mixing ra- Recently, Akritidis et al. (2018) evaluated stratosphere-to- tios, i.e., > 70 ppbv (off the scale in the time-series plot) for troposphere transport processes represented by the Coper- 23 h were predicted by TCR-2, which was an overestimation nicus Atmosphere Monitoring Service (CAMS) system, but compared with the observations. Except for 2 h on 9 October evaluation of transport and transformation processes for tro- 2014, these were always in July (in 2012, 2013, and 2014). pospheric O3 over oceans has not been reported with reanaly- All were found within 200 km east of Japan’s main islands, sis. Here, a successful comparison was made for the first time suggesting overestimation of photochemical O3 production at the daily or finer timescale. The regression line for the data during long-range transport in TCR-2. set, i.e., [TCR-2, ppbv] = (6.90±0.15)+(0.71±0.01)× [obs, With such case-dependent reproducibility in mind, Fig. 1c ppbv], suggests a statistically significant positive intercept summarizes the overall geographical distribution of the on the y axis (i.e., TCR-2) and a slope of less than unity. reanalysis/observation ratios for O3 mixing ratios. For clar- The result was unchanged even when MR14-01 and cases ity, the data were limited to cases of marine origins, where with > 70 ppbv in TCR-2 were included. The green circles the differences between the TCR-predicted and -observed in Fig. 5 represent data from the Arctic region (> 70◦ N) and CO mixing ratios were less than 50 ppbv (N = 5662), in con- clearly suggest an underestimation by TCR-2. In contrast, the trast to Fig. 1a, b, where all data (N = 11 666) were included. blue circles from the western Pacific equatorial region (125– The model’s underestimation in the Arctic Ocean and over- 165◦ E, 10◦ S to 25◦ N) fell on the opposite side, with re- estimation over the oceans south of Japan (western Pacific spect to the 1 : 1 line, indicating an overestimation by TCR-2. equatorial or subtropical regions) are clearly shown. These These two aspects will be discussed in detail in the following features will be discussed in Sect. 3.3. sections. Figure 4 shows the latitudinal distribution of the observed and TCR-2 O3 mixing ratios and their ratios. In Fig. 4a, the 3.3 Specific analysis with event or regional focuses: data were again limited to cases of marine origins, where Implications for processes the differences between the model-derived and observed CO mixing ratios were less than 50 ppbv (N = 5662). The vari- In this section, more detailed comparisons between observa- ability shown here reflects seasonality and cases of long- tions and simulations are made to shed light on the under- range transport from continents over 120 h. The range of lying mechanisms determining O3 mixing ratio levels and TCR-2/observation ratios (shown in red in Fig. 4b) nar- distributions. rowed when TCR-2 successfully captured the variability. Data selection (N = 5662) also contributed to narrowing of 3.3.1 Long-range transport events with photochemical the range (grey points indicate without data selection). The production ratios binned by latitudes indicate that TCR-2 tended to give underestimations at high northern latitudes and overestima- We selected events with simultaneous increases in CO and tions at low latitudes. The 10th, 50th (median), and 90th per- O3 levels or those with at least evident CO peaks. We then centiles (range shown as bars) of the ratios at high latitudes assessed the reproducibility of the peak mixing ratios and ◦ (> 70 N) were 0.62, 0.81, and 0.94 (N = 876); the range was 1O3/1CO ratios in TCR-2; the 1O3/1CO ratio is an index off unity. The medians for low latitudes (0–10, 10–20, and of the efficiency of photochemical production of O3 from CO 20–30◦ N) were 1.12 (N = 1061), 1.28 (N = 268), and 1.28 as a precursor. In total, 23 cases were selected (Table 2 and (N = 195), respectively. magenta rectangles in Fig. 2a). The two cases discussed be- Figure 5 shows a scatterplot of the comparison. The data low were studied in depth. set was re-expanded by removing the criteria of marine air Figure 6 shows the time evolution of the O3 and CO mix- mass selection and CO differences (i.e., N = 11 666) to show ing ratios from observations and TCR-2 during the period the overall correlation between the observed and TCR-2 data 16–19 March 2014, when the vessel returned to Japan from over the full range. The square of the correlation coeffi- the equatorial Pacific during MR14-02. The observational cient (R2) was 0.59; this increased to 0.62 when clear out- data along the entire track are shown, with the exact po-

Atmos. Chem. Phys., 19, 7233–7254, 2019 www.atmos-chem-phys.net/19/7233/2019/ Y. Kanaya et al.: Ozone and carbon monoxide over open oceans: observations and model evaluation 7241 max 3 max O 3 15 101.606 87.5 101.908 38.2 102.7 116.403 33.1 40.0 117.2 137.401 26.0 43.1 129.2 331.203 38.7 51.1 269.7 137.401 40.9 52.8 125.3 299.101 45.8 35.4 219.0 132.201 37.3 66.6 208.0 249.402 56.3 48.2 220.0 119.004 47.9 38.0 116.1 154.4 37.2 35.4 145.1 31.5 55.6 46.4 ...... CO COmax COmax O 0 0 0 0 0 0 0 0 0 0 0 /1 ± ± ± ± ± ± ± ± ± ± ± 3 O 96 12 86 15 01 51 06 23 14 15 23 ...... 0 − R 1 30 . 0 − CO is ppbv/ppbv). /1 3 O 04 0.6803 0 06 0.8504 0 0.5801 0 0.2903 0 0.9301 0 0.7509 0 0.9201 0 0.9304 0 0.7003 0 0.67 0 1 ...... CO 0 0 0 0 0 0 0 0 0 0 0 /1 ± ± ± ± ± ± ± ± ± ± ± 3 O 42 28 54 32 03 34 11 38 11 53 44 ...... R 1 E) (obs) (obs) (TCR-2) (TCR-2) (obs) (TCR-2) (obs) (TCR-2) ◦ N) ( ◦ 41.32–45.22 151.81–162.71 0.8154.47–56.59 0 182.07–193.25 0.7956.95–65.12 0 191.36–192.82 0.8040.08–40.88 0 143.72–154.34 0.7525.21–31.33 0 126.85–136.28 0.6611.51–18.95 0 151.64–154.58 0.8325.08–34.12 0 145.21–149.15 0.8642.67–45.32 0 152.68–157.02 0.5746.99–47.01 0 171.62–177.97 0.9051.15–53.38 0 208.00–221.14 0.8726.61–32.60 0 141.81–149.90 0.92 0 22:00 UTC 17 Aug 2013 12:00 UTC 25 Aug 2013 22:00 UTC 06 Oct 2013 23:00 UTC 18 Oct 2013 15:00 UTC 14 Jan 2014 00:00 UTC 15 Mar 2014 00:00 UTC 19 Mar 2014 10:00 UTC 26 Jul 2014 00:00 UTC 04 Aug 2014 00:00 UTC 27 Aug 2014 00:00 UTC 10 Nov 2014 time time ( 15 Aug 2013 23 Aug 2013 05 Oct 2013 16 Oct 2013 12 Jan 2014 13 Mar 2014 17 Mar 2014 24 Jul 2014 02 Aug 2014 25 Aug 2014 08 Nov 2014 Cases of long-range transport events used for examination of photochemistry (unit for Case StartA 22:00 UTC B End 12:00 UTC C 00:00 UTC D Latitude 23:00 UTC E 15:00 UTC F 00:00 UTC G 00:00 UTC H 13:00 UTC I 00:00 UTC J 00:00 UTC K 00:00 UTC Table 2. www.atmos-chem-phys.net/19/7233/2019/ Atmos. Chem. Phys., 19, 7233–7254, 2019 7242 Y. Kanaya et al.: Ozone and carbon monoxide over open oceans: observations and model evaluation al 2. Table 00 UTC 00:00 W UTC 12:00 V UTC 12:00 U UTC 01:00 T UTC 08:00 S UTC 04:00 R UTC 18:00 Q UTC 14:00 Longitude P UTC 00:00 Latitude O UTC 17:00 N UTC 00:00 End M UTC 02:00 L Start Case Continued. ietm ( time time 0Mr2017 Mar 20 2016 Dec 03 2016 Sep 27 2016 Sep 25 2016 Jan 23 2015 Dec 27 2015 Dec 16 2015 Nov 16 2015 Oct 05 2015 Feb 21 2015 Feb 18 2015 Feb 07 2Mr2017 Mar 22 UTC 00:00 2016 Dec 05 UTC 10:00 2016 Sep 29 UTC 12:00 2016 Sep 27 UTC 01:00 2016 Jan 24 UTC 20:00 2015 Dec 29 UTC 04:00 2015 Dec 18 UTC 15:00 2015 Nov 18 UTC 12:00 2015 Oct 06 UTC 17:00 2015 Feb 23 UTC 17:00 2015 Feb 20 UTC 00:00 2015 Feb 08 UTC 21:00 − 24 98–77 4.3126 .10 0.81 147.83–152.62 19.86–27.70 0 0.00 161.78–171.57 47.42–53.85 173.23–184.47 54.78–61.49 138.91–139.94 31.97–35.03 0 0.76 192.01–193.51 53.98–60.57 0 139.89–142.33 0.86 34.29–40.27 123.50–131.79 24.42–30.05 − − − .61.6164–3.006 0 0.67 136.43–137.00 7.66–12.46 . 6 9 1 82.6105–1.709 0 0.90 110.59–112.77 78–21.16 . . . 440 0.1122 .90 0.39 0 101.01–102.27 0.82 14–4.04 114.13–119.13 21–0.19 0 0.95 89.95–90.19 60–2.16 ◦ )( N) ◦ )(b)(b)(C-)(C-)(b)(C-)(b)(TCR-2) (obs) (TCR-2) (obs) (TCR-2) (TCR-2) (obs) (obs) E) − − − 0 0 0 . . . 74 40 27 1 R − − − 0 0 0 . . 03 05 ...... 02 03 25 00 38 24 33 09 29 21 O ± ± 3 ± ± ± ± ± ± ± ± ± ± /1 0 0 . 0 0 . 0 0 0 0 0 0 0 0 004 0 0.19 004 CO ...... 01 02 308 0 0.83 03 01 0 0.38 05 409 0 0.97 04 308 0 0.89 03 0 04 0.83 03 0 0.96 01 − − − − − 0 0 0 0 0 . . . . . 78 74 63 20 75 1 R − − − − − 0 0 0 0 0 . 03 ...... 02 13 10 16 21 09 04 60 44 37 60 O ± 3 ± ± ± ± ± ± ± ± ± ± ± /1 0 0 0 0 0 0 0 0 0 0 0 0 . 0 472441. 17.5 18.8 214.4 94.7 005 OCmxCmxO COmax COmax CO ...... 23072215. 51.5 58.9 222.1 390.7 02 22482466. 59.0 63.0 214.6 36.1 214.8 43.6 45.3 02 139.6 47.9 46.3 317.9 161.4 46.4 01 555.7 168.5 02 357.8 05 36.1 46.1 52.9 126.2 53.6 127.3 220.6 03 478.6 03 39. 912. 34.8 25.1 99.1 92.7 03 38. 312. 37.3 28.3 93.1 48.7 82.7 28.9 03 185.0 148.8 04 24.4 31.8 105.7 181.1 03 3 a O max 3 max

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Figure 4. (a) Latitudinal distribution of O3 mixing ratios from observation (black) and TCR-2 (red). Data are limited to cases of marine origins where difference between predicted and observed CO mixing ratios was less than 50 ppbv (N = 5647). (b) Latitudinal distribution of ◦ TCR-2/observation ratio for O3 (light-red dots) and binned medians (ranges are from 10th to 90th percentile) over 10 . Gray dots represent all cases without data selection.

23.69◦ N, 149.72◦ E, the CO mixing ratio peaked at around 284 ppbv. The geographical distribution of surface O3 and CO in TCR-2 implied that this was a tongue-shaped pol- lution event originating from mainland southeast Asia (for- merly the Indochina Peninsula) and extending to the east; however, it was not. Instead, as inferred from the backward trajectories (Fig. S1g), weather charts, and time evolution of CO distributions from TCR-2 (Fig. 6), it should be in- terpreted as a belt of pollution originating from east Asia, present at the south edge of a high-pressure system moving toward the southeast. An O3 peak of 54.2 ppbv occurred 10 h later, which was also captured by TCR-2. A second CO peak occurred the next day, at 19:00 UTC on 17 March 2014, at ◦ ◦ 28.56 N, 147.68 E; in this case an O3 peak of 66.2 ppbv oc- curred just 1 h before. TCR-2 suggested that the plume origi- nated from east Asia and was transported to the east from the continent and then to the south, under the influence of an- other high-pressure system traveling over Japan and a low- Figure 5. Scatterplot of observed and reanalysis O3 mixing ratios. pressure system that followed (see the second row panel in Gray circles include all data (N = 11 666), red circles are cases Fig. 6 for 01:00 UTC on 17 March 2014). The timing and lo- in which data from MR14-01 and extreme cases in which TCR-2 exceeded 70 ppbv were removed. Green circles indicate data from cation of the third peak were also well predicted; a CO peak ◦ of 273 ppbv occurred at 17:00 UTC on 18 March 2014, at Arctic region (> 70 N) and blue circles indicate data from domain ◦ ◦ 2 (125–165◦ E, 10◦ S to 25◦ N). 32.88 N, 145.77 E, 3 h after the O3 peak of 66.6 ppbv (the highest in the data set). In this case, the air mass traveled directly from central east China, with a large precursor emis- sion (see the distribution of grids with high CO emissions sition of R/V Mirai at that time marked by a black circle. in the panel for 01:00 UTC on 19 March 2014) via a quick This part of the cruise has already been briefly mentioned westerly flow under the influence of passage of a cold front. in Sect. 3.2; here, the origins of pollution and the photo- The 1O3/1CO ratio, calculated as the slope of the regres- chemical states for three episodes with increased mixing ra- sion line in a scatterplot of hourly mixing ratios of O3 and tios are discussed. First, at 09:00 UTC on 16 March 2014, at www.atmos-chem-phys.net/19/7233/2019/ Atmos. Chem. Phys., 19, 7233–7254, 2019 7244 Y. Kanaya et al.: Ozone and carbon monoxide over open oceans: observations and model evaluation

Figure 6. Temporal evolution of surface CO and O3 distribution from TCR-2 (colored open squares) and from observations on R/V Mirai (all data, position of vessel is black circle) during MR14-02 (from 16 to 19 March 2014). Black circles in the bottom-left CO panel indicate locations with high anthropogenic CO emissions (EDGAR).

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CO between 00:00 UTC on 17 March 2014 and 00:00 UTC February for cases N and S, and weak co-emission of NOx 19 on March 2014, was 0.11 ± 0.01 ppbv/ppbv (R = 0.83) from forest fires for case T, could cause the observed negative for observations and 0.06 ± 0.01 ppbv/ppbv (R = 0.75) for slopes. Processes other than daytime photochemistry (e.g., TCR-2 (Table 2, case G). The underestimation of O3 peaks nocturnal chemistry) might also have been important. by TCR-2 (maximum 56.3 ppbv) is attributable to a combi- Figure 8 shows the correlation between the observed and nation of less efficient production of O3 and underestimation reanalysis 1O3/1CO ratios. The reasonable correlation, of CO peaks by TCR-2 (maximum 219 ppbv). with a slope of 1.15 ± 0.29 and R2 = 0.42, suggests that Figure 7 shows a similar time evolution during MR14-04 TCR-2 reproduced the state of O3 production fairly well for Leg 2, when a plume reached the central Pacific from the various cases in different geographical domains in different Asian continent about 5000 km away. The 1O3/1CO ratio seasons. Case B is an outlier in terms of correlation: obser- from 00:00 UTC on 2 August 2014 to 00:00 UTC on 4 Au- vations and TCR-2 yielded 1O3/1CO ratios of 0.28 ± 0.03 gust 2014 was 0.11±0.01 ppbv/ppbv (R = 0.90) for observa- and −0.12±0.06 ppbv/ppbv, respectively. This was recorded tions and 0.14 ± 0.01 ppbv/ppbv (R = 0.93) for TCR-2. The at the center of the Bering Sea, where TCR-2 failed to re- maximum CO and O3 mixing ratios were 249 and 38.0 ppbv, produce the coinciding increases in the observed O3 and CO respectively, for observations, and 220 and 37.2 ppbv, respec- mixing ratios. tively, for TCR-2 (Table 2, case I). The pollution source was The observed and simulated ranges of the 1O3/1CO ra- probably forest fires in the far east of Russia (shown by plus tios are in accordance with previously reported data. On signs in the upper-left panel of Fig. 7) with a smaller contri- the Azores in the central Atlantic (38.73◦ N) in spring and bution from anthropogenic emissions from east Asia. Specif- on Sable Island (43.93◦ N) in Atlantic Canada in summer, ically, on 26 July 2014, the head of a plume extending from the 1O3/1CO ratios were uniform, at 0.3–0.4 ppbv/ppbv the forest fires arrived in northern Japan (see Zhu et al., 2019 (Parrish et al., 1998). For TRACE-P aircraft measure- and references therein for details) and affected our ship ob- ments, Hsu et al. (2004) reported smaller values, i.e., servations. The main body of the plume arrived from the west 0.08 ppbv/ppbv in the tropics and 0.03 ppbv/ppbv in the ex- and traveled with a migrating high-pressure system until 6 tratropics, with CO > 200 ppbv. Weiss-Penzias et al. (2006) August 2014. The observed CO and O3 mixing ratios de- reported 0.22 ppbv/ppbv in April and May 2004 for two creased during the period 29 July to 1 August 2014, when long-range transport events that reached a mountain on the the vessel was located at the center of a low-pressure sys- west coast of the United States from Asia. Tanimoto et tem traveling to the east. After the low-pressure system had al. (2008) summarized the range as being from slightly weakened, the plume was still present in its southern part negative to ∼ 0.4 ppbv/ppbv when observing Siberian fire and was pushed northeast under the influence of the high- plumes at Rishiri Island. Zhang et al. (2018) documented the pressure system in the south, which again affected the ship 1O3/1CO ratios at Pico Mountain in the Atlantic Ocean observations during 2 and 3 August 2014, in the middle of and found that the ratios for anthropogenic pollution were the North Pacific. higher (0.45–0.71 ppbv/ppbv) than those for observations af- Table 2 summarizes the results from all 23 cases, including fected by wildfires (0.12–0.71 ppbv/ppbv). They suggested the two events discussed above (cases F and G from MR14- that the low ratios from wildfires could be the result of lower 02 and cases H and I from MR14-04 Leg 2). The span of the NOx/CO emission ratios compared with those for anthro- study area was from the Indian Ocean in the Southern Hemi- pogenic sources. sphere, and the central equatorial Pacific Ocean to the Bering Sea (see magenta rectangles in Fig. 2a). In most cases, the 3.3.2 Arctic processes observed 1O3/1CO slopes were positive, suggesting pho- ◦ tochemical buildup of O3 with emissions of CO. The ranges In the Arctic Ocean (> 70 N), the CO mixing ratios were were well reproduced by TCR-2. It is interesting to note that regularly close to the background and stable (101 ± 10 ppbv, negative slopes for 1O3/1CO were found for at least three Fig. S1d, j, n, and s), suggesting that the measurements were cases and that these were also well captured by TCR-2. These not affected by strong pollution events. The average observed were the cases where very high CO levels were recorded O3 mixing ratio was 31.3 ppbv (N = 1804) and the reanal- (479, 358, and 556 ppbv for cases N, S, and T, respectively). ysis significantly underestimated this (24.6 ppbv) based on The strong negative correlation for case N was influenced Welch’s t test (p<0.001). The magnitude of the relation- by the low O3 mixing ratios (11.2 ppbv) recorded with high ship was common for all 4 years of measurements (Fig. 9). CO levels. When such irregular points were removed, the ob- A low bias with TCR-2 was also clear for cumulative fre- served slope was 0.01 ± 0.01 ppbv/ppbv. For case S, a strong quency distributions of hourly O3 mixing ratios from ob- CO peak occurred in the south of Japan (∼ 200 km off the servations (black, N = 1031) and TCR-2 (red) in domain 1 ◦ ◦ coast) on 23 January 2016, without an O3 increase (Fig. S1r). (72.5–77.5 N, 190–205 E) in September (Fig. 10). The fre- For case T, a plume from a Russian forest fire affected the quency distributions for eight model members of ACCMIP observations over the Bering Sea (Fig. S1s). Relatively fresh and their ensemble median (magenta) are also included in air pollution from nearby ships or weak UV in January and Fig. 10. The median was close to that for TCR-2 and sim- www.atmos-chem-phys.net/19/7233/2019/ Atmos. Chem. Phys., 19, 7233–7254, 2019 7246 Y. Kanaya et al.: Ozone and carbon monoxide over open oceans: observations and model evaluation

Figure 7. Temporal evolution of surface CO and O3 distribution from TCR-2 (colored open squares) and from observations on R/V Mirai (all data; position of vessel is shown by black circle) during MR14-04 Leg 2 (from 26 July to 3 August 2014). Plus signs in the top-left panel show points with high carbon emissions from wildfires (GFED).

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Figure 10. Cumulative relative frequency distributions of O3 mix- ing ratios from observations (black), TCR-2 (red), and members and ensemble median of ACCMIP in the Arctic grid 1 (72.5–77.5◦ N, 190–205◦ E) in September.

1 /1 Figure 8. Correlations between O3 CO ratios from observa- During the MR14-05 cruise, 10 O3 sondes were launched tions and TCR-2. every other day at 22:00 UTC during the period 6–24 September 2014 (Inoue et al., 2018). The average vertical profile was compared with that from TCR-2 at the nearest grid (Fig. 11) to investigate the altitude to which this low bias of TCR-2 continued. At the lowest altitude near the surface, the underestimation by TCR-2 against the O3 sonde observa- tions was evident. However, the gap only continued to about 850 hPa, at which the two mixing ratios crossed over, and TCR-2 gave higher mixing ratios at higher altitudes. This suggests that the missing process was only important for the boundary layer, not for the entire troposphere. Inoue et al. (2018) compared the O3 sonde profiles with ERA-Interim (ERA-I) products, with a focus on troposphere–stratosphere exchange. They found that in the upper-troposphere ERA-I had a high bias against observations, similarly to the case for TCR-2; this confirms that the underestimation by the model Figure 9. Repeated underestimations of O3 mixing ratios ranges by ◦ for the surface did not continue into the tropopause. One TCR-2 relative to observed values in the Arctic region (> 70 N). possibility is that the model’s vertical (downward) mixing Boxes and horizontal bars indicate 75 %, 50 % (median), and 25 %, near the top of the boundary layer was too weak: this mix- and whiskers indicate 90 % and 10 %. Circles are averages. ing would otherwise have effectively carried the O3-rich air mass from higher altitudes. Another possibility is that dry deposition on the surface of the Arctic Ocean by the model −1 ilarly significantly underestimated, although three members was too fast. The vd, ∼ 0.04 cm s over the Arctic open (GEOSCCM, GFDL-AM3, and GISS-E2-R) showed better ocean in September for CHASER (TCR-2), is on the high agreement with observations. These analyses suggest that, side of ∼ 0.01–0.05 cm s−1, a range adopted into global at- in the simulations, the sources were too weak or the losses mospheric chemistry models (see Fig. 4 of Hardacre et al., were too strong. The average diurnal variations were gener- 2015). Ganzeveld et al. (2009) discussed a sensitivity model −1 ally almost flat (the variability was within 5 % of the average) run, shifting their standard vd of 0.05 to 0.01 cm s , which for observations and TCR-2 (not shown), suggesting that the substantially increased surface ozone concentrations by up to missing processes did not show significant diurnal variabil- 60% in high-latitude regions. ity. At high latitudes, the assimilated measurements have ei- At Barrow (71.32◦ N, 156.6◦ W), the nearest ground-based ther low quality or low sensitivity in the troposphere, while site, the monthly average O3 mixing ratios in September the optimization of precursors emissions generally has lim- were 29.8 and 29.1 ppbv, in 2013 and 2014, respectively ited impacts on ozone. The reanalysis ozone over the Arctic (McClure-Begley et al., 2014). These values are close to our Ocean can be similar to the model predictions, except when observations over oceans, and the model ensemble tended poleward transports are strong enough to propagate observa- to underestimate mixing ratios in September (AMAP, 2015), tional information from low latitudes and midlatitudes. similarly to our case. www.atmos-chem-phys.net/19/7233/2019/ Atmos. Chem. Phys., 19, 7233–7254, 2019 7248 Y. Kanaya et al.: Ozone and carbon monoxide over open oceans: observations and model evaluation

Figure 11. Average profile from O3 soundings (blue) and that from TCR-2 (red). Average from surface observations on R/V Mirai is shown as black circle.

3.3.3 O3 levels below 10 ppbv at low latitudes Figure 12. Cumulative relative frequency distributions of O3 mix- ing ratios from observations (black), TCR-2 (red), and members Figures 1c, 4, and 5 show that TCR-2 tended to overesti- and ensemble median of ACCMIP for domain 3 (0–15◦ N and 150– ◦ mate O3 mixing ratios over the western Pacific equatorial 165 E) in (a) March and (b) December. region. For the whole global data set, TCR-2 predicted O3 levels below 10 ppbv O3 during 262 h, which is much less than the observed duration, i.e., 800 h. The occurrence fre- the model results may reflect the impact of large variations quencies in the region 125–165◦ E, 10◦ S to 25◦ N (defined in transport, particularly in March. Because of the lack of di- as domain 2, N = 2258) were large, namely 295 and 205 h rect constraints over the remote oceans on near-surface mix- for observations and TCR-2 predictions, respectively. When ing ratios in the current satellite observing systems, the sys- the studied region was further narrowed to 150–165◦ E and tematic mismatches imply requirements for exploring model 0–15◦ N (defined as domain 3, N = 657), the discrepancy in- error sources to improve the reanalysis quality. creased again, i.e., 199 and 80 h for observations and pre- The average relative diurnal variations normalized to the dictions, respectively. In March and December, observations maximum mixing ratios during these 2 months (Fig. 13, were frequently conducted in domain 3 (N = 211 and 321, x axis is UTC+11 h, adjusted to local time for the selected respectively). Figure 12 shows the cumulative relative fre- region) showed a pattern of daytime decreases, suggesting quency distributions for observations, and the TCR-2 and photochemical destruction. However, the observed decrease ACCMIP models for these two months. In March (Fig. 12a), was stronger (15 %) and earlier than those simulated in the the observed O3 mixing ratios in the low ranges (< 30th per- TCR-2 and ACCMIP runs, in which the HOx cycle was pri- centiles) were as low as 5 ppbv; these were overestimated by marily responsible for photochemical destruction. This fea- TCR-2. The shape of the distribution was in better agreement ture may indicate O3 loss via a different process, e.g., halo- for higher ranges (30th to 100th percentiles). The ensemble gen chemistry, which is not included in any of the model sim- medians for the ACCMIP runs were higher than the obser- ulations considered in this study. vations for any of the percentiles, whereas CESM-CAM- To obtain further insights into the regions in which this superfast, GISS-E2-R, GEOSCCM, and MOCAGE better additional loss could be important, the differences between captured features of the observed low mixing ratios (at higher the O3 levels predicted by TCR-2 and the observed levels percentiles GEOSCCM and MOCAGE gave mixing ratios were calculated and the correlations with the residence times that were too high). For December (Fig. 12b), the perfor- (in the daytime) of back trajectories in 15◦ × 15◦ grid re- mances of the models were poorer: although CESM-CAM- gions around domain 3 were examined. Use of the residence superfast and GISS-E2-R again captured the observed dis- time during the day can be justified because the destruction tributions in low ranges, all others, including the ACCMIP probably occurred in the daytime (Fig. 13). Figure S2 shows ensemble median and TCR-2, overestimated the mixing ra- the results for 17 regions, covering 120–195◦ E and 15◦ S tios for any of the percentiles. The large variations among to 45◦ N. We found that the residence time in the grid re-

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Figure 13. Diurnal variation patterns relative to maximum mixing ratios from observations (black), TCR-2 (red), and members and ensemble median of ACCMIP for domain 3 (0–15◦ N and 150– ◦ 165 E). Data from March and December are merged. Figure 14. High biases in TCR-2 with respect to observations in domain 2 (10◦ S to 25◦ N, 125–165◦ E) show positive correlations with daytime residence times in grid 15–30◦ N and 165–180◦ E. gion 165–180◦ E and 15–30◦ N, located northeast of domain 3, had the largest positive correlation coefficient (Fig. 14). This suggests that this region is a possible hotspot for addi- ratios at Kwajalein Island (8.72◦ N, 167.73◦ E), Republic of tional loss. It is worth noting that data from all five cruises the Marshall Islands, located near our hotspot grid, during contributed to the positive correlation, which suggests that July, August, and September 1999, were lower than 10 ppbv the relationship is reproducible. The slope of the regression throughout 24 h, with an afternoon decrease of about 1 ppbv. line was 0.25 ppbv h−1. This corresponds to the possible loss Gómez Martín et al. (2016) reported year-round continu- ◦ rate in the grid that best explains the discrepancy between ous observations of surface O3 at San Cristóbal (0.90 S, observations and TCR-2 predictions. If the rate is attributed 89.61◦ W) and at Puerto Villamil, Isabela Island (0.96◦ S, to dry deposition on the sea surface, a deposition veloc- 90.97◦ W), in the Galápagos Islands in the equatorial east- ity as high as 0.33 cm s−1 is required, assuming a boundary ern Pacific. Daily averages as low as 5–6 ppbv were observed layer height of 1000 m and an average O3 mixing ratio of during the period February to May. During the Malaspina cir- 17.4 ppbv. This high velocity is not supported by previous cumnavigation in 2010, O3 mixing ratios as low as 3.4 ppbv studies (e.g., Ganzeveld et al., 2009; Hardacre et al., 2015). were detected around the central Pacific equatorial region Such a loss rate can be more easily explained by bromine (Prados-Roman et al., 2015). During PEM-West A in Octo- and/or iodine chemistry in the atmosphere (e.g., Saiz-Lopez ber 1991, Singh et al. (1996) reported O3 levels as low as 8– et al., 2012, 2014). We observed elevated iodine monoxide 9 ppbv from aircraft measurements at altitudes of 0.3–0.5 km (IO) radical concentrations with a MAX-DOAS instrument in the region 0–20◦ N in the western and central Pacific. It is aboard R/V Mirai during the cruises included in the analy- worth noting that the O3 levels over the Atlantic were typi- sis in Fig. 14. Further analysis will be reported in a future cally higher, e.g., 30–35 ppbv (Read et al., 2008), even when publication. halogen-mediated destruction was considered. In these stud- Substantially reduced O3 levels (< 10 ppbv) have been re- ies, detailed statistical comparisons of the observed O3 levels ported in the marine boundary layer over the equatorial Pa- with chemistry–climate model simulations or reanalysis data cific. Johnson et al. (1990) found near-zero (3 ppbv or less) as focused here have not been achieved. Conducting contin- O3 mixing ratios in the central equatorial Pacific during April uous observations of O3 during a large number of cruise legs and May. Kley et al. (1996) observed similar events in March was useful for obtaining a large data set for performing de- 1993, with mixing ratios occasionally reaching 3–5 ppbv, tailed statistical analysis. from O3 soundings in a region between the Solomon Islands The influence of halogen (bromine and/or iodine) chem- ◦ ◦ ◦ ◦ (9.4 S, 160.1 E) and Christmas Island (2 N, 157.5 W). istry on O3 levels has been studied using model simulations Takashima et al. (2008) reported substantially reduced O3 at assumed (e.g., Davis et al., 1996; Hu et al., 2010) and ob- events throughout the year on Christmas Island. Rex et served levels of halogen compounds (Mahajan et al., 2012; al. (2014) used a combination of O3 sounding data from Dix et al., 2013; Großmann et al., 2013; Prados-Roman et al., the TransBrom cruise of R/V Sonne in October 2009, atmo- 2015; Koenig et al., 2017) over the Pacific. For example, for spheric chemistry models, and satellite observations to iden- bromine chemistry, Hu et al. (2010) estimated a photochem- −1 tify a region with strong O3 depletion in the marine bound- ical loss rate of up to 0.12 ppbv h . A loss of about 0.4 ppbv ary layer at 0–10◦ N along the north–south cruise track (at d−1 can be attributed to halogen chemistry in the marine around 150◦ E). This is in good agreement with our obser- boundary layer south of Hawaii (Dix et al., 2013). From vations. Hu et al. (2010) reported that average O3 mixing CAM-chem-based global model simulations, Saiz-Lopez et www.atmos-chem-phys.net/19/7233/2019/ Atmos. Chem. Phys., 19, 7233–7254, 2019 7250 Y. Kanaya et al.: Ozone and carbon monoxide over open oceans: observations and model evaluation al. (2012) estimated an annually integrated rate of surface tinue) is open and complements the TOAR data collection −1 O3 loss through halogen chemistry as ∼ 0.15 ppbv h in and will be useful for critically evaluating global-scale atmo- the daytime, over the region 20◦ S to 20◦ N. On the basis spheric chemistry model simulations, including those from of GEOS-Chem, Sherwen et al. (2016) suggested that halo- CCMI, AerChemMIP (Collins et al., 2017), and future inter- gen chemistry would reduce surface O3 levels by ∼ 3–5 ppbv model comparisons. over our domain 3. These loss rates caused by halogen chem- istry are in fair agreement with the required additional loss −1 rate, i.e., ∼ 0.25 ppbv h , estimated in this study. Data availability. The observational data set for O3 and CO ob- Our observational O3 data set with a large geographical tained on R/V Mirai for the study period (2012–2017) is col- coverage will be useful for evaluating up-to-date model sim- lectively available from https://ebcrpa.jamstec.go.jp/atmoscomp/ ulations with inclusion of halogen chemistry. Analysis at obsdata/ (last access: 23 May 2019) (Atmospheric Composition midlatitude regions over the Pacific are also of interest be- Research Group, 2019) as a single text file and from http://www. godac.jamstec.go.jp/darwin/e (last access: 23 May 2019) (DAR- cause the importance of halogen chemistry in this region has WIN, 2019) for individual cruise legs. TCR-2 reanalysis data are been indicated (e.g., Nagao et al., 1999; Galbally et al., 2000; available from http://ebcrpa.jamstec.go.jp/tcr2/download.html (last Watanabe et al., 2005). access: 23 May 2019) (JAMSTEC, 2019).

4 Summary and outlook Supplement. The supplement related to this article is available online at: https://doi.org/10.5194/acp-19-7233-2019-supplement. We compiled a large data set of shipborne in situ observa- tions of O3 and CO levels with a 1 h resolution, which were recorded on R/V Mirai over the Arctic, Bering, Pacific, In- Author contributions. YuKa designed the study, conducted analy- dian, and Southern oceans from 67◦ S to 75◦ N, during the ses, wrote the manuscript, managed the instruments and created the period 2012 to 2017. We used the data set to evaluate tropo- observational data set. KM, TS, and KeS created TCR-2 data. FT, spheric chemistry reanalysis data from TCR-2 and ACCMIP TM, HT, YuKo, XP, and SK substantially contributed to shipborne model simulations. TCR-2 captured the basic features of the observations and preparation. HT and SK also provided supporting observations, including the latitudinal gradient and air mass data from MAX-DOAS observations. JI, KaS, and KO conducted shipborne ozone soundings and provided the data. All co-authors exchange, and therefore enabled interpretation of observa- provided professional comments to improve the manuscript. tions regarding transport and pollution sources. Correlations with observations were sufficient (R2 up to 0.62 for hourly data and 0.67 for daily data). This suggests an excellent per- Competing interests. The authors declare that they have no conflict formance by TCR-2 in representing the temporal and geo- of interest. graphical distributions of surface O3. For over 23 long-range transport events with CO and/or O3 buildup, variations in the 1O3/1CO ratios were well reproduced by TCR-2. This Acknowledgements. We gratefully acknowledge assistance from suggests that the nature of photochemical evolution during the Principal Investigators of all cruises and support from Global transport of pollution plumes was also well captured. How- Ocean Development Inc. and Nippon Marine Enterprise, Ltd. Part ever, two major discrepancies were identified: in the Arctic of the research was carried out at the Jet Propulsion Laboratory, Cal- (> 70◦ N) in September, TCR-2 and the ensemble median of ifornia Institute of Technology, under a contract with the National Aeronautics and Space Administration. We thank Helen McPher- model runs of ACCMIP tended to underestimate O3 levels. son, PhD, from Edanz Group (https://www.edanzediting.com, last From analysis of O3 sonde measurements, we concluded that the gap was related to processes relevant to the boundary access: 27 May 2019) for editing a draft of this manuscript. layer: downward mixing from the free troposphere, with a higher O abundance, might have been too weak in the mod- 3 Financial support. This research has been supported by the Min- els. For TCR-2, dry deposition on the Arctic Ocean surface istry of Education, Culture, Sports, Science and Technology might have been too fast. Conversely, in the western Pacific (MEXT) (Coordination Funds for Promoting AeroSpace Utilization equatorial region, TCR-2 and ACCMIP simulations signifi- and the Arctic Challenge for Sustainability (ArCS) project grants), cantly overestimated the observed O3 levels, which were of- the MEXT/JSPS KAKENHI (grant nos. 24241009, 18H04143, and ten less than 10 ppbv. The minimum in the observed diurnal 18H01285), and the Ministry of the Environment, Japan (Environ- pattern occurred earlier than those in the models. The gap of ment Research and Technology Development Fund, grant no. 2- mixing ratios correlated with the residence time of trajecto- 1803). ries over a particular grid, i.e., 15–30◦ N, 165–180◦ E. These analyses indicate the importance of halogen chemistry, which is not accounted for in the models, and the region in which it Review statement. This paper was edited by Neil Harris and re- is active. The data set from our observations (which will con- viewed by two anonymous referees.

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